Source code for ants.viz.render_surface_function

__all__ = ["render_surface_function"]

import os
import warnings
import skimage.measure
import webcolors as wc
from ..registration import resample_image

    import chart_studio.plotly as py
    from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
    from plotly.graph_objs import *
    from plotly import figure_factory as FF
        "Cant import Plotly. Install it `pip install chart_studio` if you want to use ants.render_surface_function"

[docs]def render_surface_function( surfimg, funcimg=None, alphasurf=0.2, alphafunc=1.0, isosurf=0.5, isofunc=0.5, smoothsurf=None, smoothfunc=None, cmapsurf="grey", cmapfunc="red", filename=None, notebook=False, auto_open=False, ): """ Render an image as a base surface and an optional collection of other image. ANTsR function: `renderSurfaceFunction` NOTE: The ANTsPy version of this function is actually completely different than the ANTsR version, although they should produce similar results. Arguments --------- surfimg : ANTsImage Input image to use as rendering substrate. funcimg : ANTsImage Input list of images to use as functional overlays. alphasurf : scalar alpha for the surface contour alphafunc : scalar alpha value for functional blobs isosurf : scalar intensity level that defines lower threshold for surface image isofunc : scalar intensity level that defines lower threshold for functional image smoothsurf : scalar (optional) smoothing for the surface image smoothfunc : scalar (optional) smoothing for the functional image cmapsurf : string color map for surface image cmapfunc : string color map for functional image filename : string where to save rendering. if None, will plot interactively notebook : boolean whether you're in a jupyter notebook. Returns ------- N/A Example ------- >>> import ants >>> mni = ants.image_read(ants.get_ants_data('mni')) >>> mnia = ants.image_read(ants.get_ants_data('mnia')) >>> ants.render_surface_function(mni, mnia, alphasurf=0.1, filename='/users/ncullen/desktop/surffnc.png') """ cmap_dict = { "grey": "Greys", "gray": "Greys", "red": "Reds", "green": "Greens", "jet": "Jet", } if surfimg.dimension != 3: raise ValueError("surfimg must be 3D") # if (filename is None) and (not notebook_render): # raise Exception('Must either 1) give filename, 2) set `html_render`=True or 3) set `notebook_render`=True') if notebook: init_notebook_mode(connected=True) fig_list = [] fig_data_list = [] surfimg = resample_image(surfimg, (3, 3, 3)) surfimg_arr = surfimg.numpy() surfverts, surffaces, _, _ = skimage.measure.marching_cubes_lewiner( surfimg_arr, isosurf, spacing=(1, 1, 1) ) surffig = FF.create_trisurf( x=surfverts[:, 0], y=surfverts[:, 1], z=surfverts[:, 2], colormap=cmap_dict.get(cmapsurf, cmapsurf), plot_edges=False, simplices=surffaces, ) surffig["data"][0].update(opacity=alphasurf) fig_list.append(surffig) fig_data_list.append([0]) if funcimg is not None: if not isinstance(funcimg, (tuple, list)): funcimg = [funcimg] if not isinstance(alphafunc, (tuple, list)): alphafunc = [alphafunc] * len(funcimg) if not isinstance(isofunc, (tuple, list)): isofunc = [isofunc] * len(funcimg) if not isinstance(cmapfunc, (tuple, list)): cmapfunc = [cmapfunc] * len(funcimg) # cmapfunc = [cmap_dict.get(c,c) for c in cmapfunc] for i in range(len(cmapfunc)): cmapfunc[i] = "rgb%s" % str(wc.name_to_rgb(cmapfunc[i])) cmapfunc[i] = [cmapfunc[i]] * 2 for func_idx, fimg in enumerate(funcimg): if fimg.dimension != 3: raise ValueError("all funcimgs must be 3D") fimg = resample_image(fimg, (3, 3, 3)) funcimg_arr = fimg.numpy() funcverts, funcfaces, _, _ = skimage.measure.marching_cubes_lewiner( funcimg_arr, isofunc[func_idx], spacing=(1, 1, 1) ) funcfig = FF.create_trisurf( x=funcverts[:, 0], y=funcverts[:, 1], z=funcverts[:, 2], plot_edges=False, simplices=funcfaces, colormap=cmapfunc[func_idx], ) funcfig["data"][0].update(opacity=alphafunc[func_idx]) fig_list.append(funcfig) fig_data_list.append([0]) if filename is not None: save_file = "png" image_filename = filename filename = image_filename.split(".")[0] + ".html" else: image_filename = "ants_plot" filename = "ants_plot.html" save_file = None try: plot( fig_data_list, image=save_file, filename=filename, image_filename=image_filename, auto_open=auto_open, ) except PermissionError: print( "PermissionError caught - are you running jupyter console? Try launching it with sudo privledges (e.g. `sudo jupyter-console`)" )